Jakov - Repository of the University of Criminal Investigation and Police Studies
University of Criminal Investigation and Police Studies
    • English
    • Српски
    • Српски (Serbia)
  • English 
    • English
    • Serbian (Cyrillic)
    • Serbian (Latin)
  • Login
View Item 
  •   Jakov
  • Jakov
  • Radovi istraživača / Researchers' publications
  • View Item
  •   Jakov
  • Jakov
  • Radovi istraživača / Researchers' publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Roadside public survey approach in black spot identification on rural roads: case study

Thumbnail
2016
732.pdf (354.3Kb)
Authors
Nešić, Miladin
Lipovac, Krsto
Vujanić, Milan
Jovanović, Dragan
Article (Published version)
Metadata
Show full item record
Abstract
This paper examines the possibility of applying the Subjective Black Spot Identification Method on state roads. A survey was conducted using interviews about 659 drivers' attitudes on the existence of Black Spots, on nine sections of state roads in the Republic of Serbia. A total of 124 locations were obtained which drivers believed were Perceived Dangerous Locations (PDLs). A set of hypotheses was defined in order to examine whether a particular PDL is a Black Spot and the test was carried out using the Bayesian Multiple Testing (BMT). Since an actual Black Spot has not been recognized as a PDL in the survey, which consequently is not subject to the BMT, new concept that includes: frequency of mishits in identifying real 'Black Spots' (RPM) and real 'non Black Spots' (RNM) and frequency of hits in identifying real 'Black Spots' (RPH) and real 'non Black Spots' (RNH) have been therefore introduced, enabling the inclusion of this outcome in the BMT. Optimisation methods have been propos...ed for the optimum threshold t selection with the minimization of the frequency of mishits (RPM and RNM) and maximization of the frequency of hits (RPH and RNH). Two operatively usable solutions have been offered here: if the consumption of resources and the effectiveness of spending of funds for identification are primarily low, then the best result is obtained using the optimisation with the minimization of the sum of mishits frequency. Then t = 24.7% (threshold of votes for selecting PDLs as Black Spots), and the ratio of correctly and wrongly selected Black Spots is 1:1.16. On the other hand, if the goal is to detect as many real Black Spots, regardless of the reduction in the effectiveness of spending of funds, then the optimisation with the equalizing of the frequencies of mishits gives the best results. In that case, t = 7.7%, and the ratio of correctly and wrongly selected Black Spots is 1:7.15.

Keywords:
black spot / pre-identification / drivers attitudes survey / perceived dangerous locations / Bayesian multiple testing / optimisation
Source:
Transport, 2016, 31, 2, 271-281
Publisher:
  • Vilnius Gedinimas Technical University
Funding / projects:
  • Development and application of risk management models on corridors VII and X from the aspect of improvement of the transportation system of Serbia (RS-36007)

DOI: 10.3846/16484142.2016.1193055

ISSN: 1648-4142

WoS: 000378916500017

Scopus: 2-s2.0-84976514692
[ Google Scholar ]
2
1
URI
http://jakov.kpu.edu.rs/handle/123456789/734
Collections
  • Radovi istraživača / Researchers' publications
Institution/Community
Jakov
TY  - JOUR
AU  - Nešić, Miladin
AU  - Lipovac, Krsto
AU  - Vujanić, Milan
AU  - Jovanović, Dragan
PY  - 2016
UR  - http://jakov.kpu.edu.rs/handle/123456789/734
AB  - This paper examines the possibility of applying the Subjective Black Spot Identification Method on state roads. A survey was conducted using interviews about 659 drivers' attitudes on the existence of Black Spots, on nine sections of state roads in the Republic of Serbia. A total of 124 locations were obtained which drivers believed were Perceived Dangerous Locations (PDLs). A set of hypotheses was defined in order to examine whether a particular PDL is a Black Spot and the test was carried out using the Bayesian Multiple Testing (BMT). Since an actual Black Spot has not been recognized as a PDL in the survey, which consequently is not subject to the BMT, new concept that includes: frequency of mishits in identifying real 'Black Spots' (RPM) and real 'non Black Spots' (RNM) and frequency of hits in identifying real 'Black Spots' (RPH) and real 'non Black Spots' (RNH) have been therefore introduced, enabling the inclusion of this outcome in the BMT. Optimisation methods have been proposed for the optimum threshold t selection with the minimization of the frequency of mishits (RPM and RNM) and maximization of the frequency of hits (RPH and RNH). Two operatively usable solutions have been offered here: if the consumption of resources and the effectiveness of spending of funds for identification are primarily low, then the best result is obtained using the optimisation with the minimization of the sum of mishits frequency. Then t = 24.7% (threshold of votes for selecting PDLs as Black Spots), and the ratio of correctly and wrongly selected Black Spots is 1:1.16. On the other hand, if the goal is to detect as many real Black Spots, regardless of the reduction in the effectiveness of spending of funds, then the optimisation with the equalizing of the frequencies of mishits gives the best results. In that case, t = 7.7%, and the ratio of correctly and wrongly selected Black Spots is 1:7.15.
PB  - Vilnius Gedinimas Technical University
T2  - Transport
T1  - Roadside public survey approach in black spot identification on rural roads: case study
VL  - 31
IS  - 2
SP  - 271
EP  - 281
DO  - 10.3846/16484142.2016.1193055
UR  - conv_1157
ER  - 
@article{
author = "Nešić, Miladin and Lipovac, Krsto and Vujanić, Milan and Jovanović, Dragan",
year = "2016",
abstract = "This paper examines the possibility of applying the Subjective Black Spot Identification Method on state roads. A survey was conducted using interviews about 659 drivers' attitudes on the existence of Black Spots, on nine sections of state roads in the Republic of Serbia. A total of 124 locations were obtained which drivers believed were Perceived Dangerous Locations (PDLs). A set of hypotheses was defined in order to examine whether a particular PDL is a Black Spot and the test was carried out using the Bayesian Multiple Testing (BMT). Since an actual Black Spot has not been recognized as a PDL in the survey, which consequently is not subject to the BMT, new concept that includes: frequency of mishits in identifying real 'Black Spots' (RPM) and real 'non Black Spots' (RNM) and frequency of hits in identifying real 'Black Spots' (RPH) and real 'non Black Spots' (RNH) have been therefore introduced, enabling the inclusion of this outcome in the BMT. Optimisation methods have been proposed for the optimum threshold t selection with the minimization of the frequency of mishits (RPM and RNM) and maximization of the frequency of hits (RPH and RNH). Two operatively usable solutions have been offered here: if the consumption of resources and the effectiveness of spending of funds for identification are primarily low, then the best result is obtained using the optimisation with the minimization of the sum of mishits frequency. Then t = 24.7% (threshold of votes for selecting PDLs as Black Spots), and the ratio of correctly and wrongly selected Black Spots is 1:1.16. On the other hand, if the goal is to detect as many real Black Spots, regardless of the reduction in the effectiveness of spending of funds, then the optimisation with the equalizing of the frequencies of mishits gives the best results. In that case, t = 7.7%, and the ratio of correctly and wrongly selected Black Spots is 1:7.15.",
publisher = "Vilnius Gedinimas Technical University",
journal = "Transport",
title = "Roadside public survey approach in black spot identification on rural roads: case study",
volume = "31",
number = "2",
pages = "271-281",
doi = "10.3846/16484142.2016.1193055",
url = "conv_1157"
}
Nešić, M., Lipovac, K., Vujanić, M.,& Jovanović, D.. (2016). Roadside public survey approach in black spot identification on rural roads: case study. in Transport
Vilnius Gedinimas Technical University., 31(2), 271-281.
https://doi.org/10.3846/16484142.2016.1193055
conv_1157
Nešić M, Lipovac K, Vujanić M, Jovanović D. Roadside public survey approach in black spot identification on rural roads: case study. in Transport. 2016;31(2):271-281.
doi:10.3846/16484142.2016.1193055
conv_1157 .
Nešić, Miladin, Lipovac, Krsto, Vujanić, Milan, Jovanović, Dragan, "Roadside public survey approach in black spot identification on rural roads: case study" in Transport, 31, no. 2 (2016):271-281,
https://doi.org/10.3846/16484142.2016.1193055 .,
conv_1157 .

DSpace software copyright © 2002-2015  DuraSpace
About Jakov | Send Feedback

OpenAIRERCUB
 

 

All of DSpaceInstitutions/communitiesAuthorsTitlesSubjectsThis institutionAuthorsTitlesSubjects

Statistics

View Usage Statistics

DSpace software copyright © 2002-2015  DuraSpace
About Jakov | Send Feedback

OpenAIRERCUB